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Codebase for reproducing the experiments of the semantic uncertainty paper (short-phrase and sentence-length experiments).
Source code of our paper MIND, ACL 2024 Long Paper
Curated tutorials and resources for Large Language Models, Text2SQL, Text2DSL、Text2API、Text2Vis and more.
A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL
华南理工大学硕博士学位论文模板(LaTeX)。Latex templates for the thesis of South China University of Technology
Implementation of "RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation".
Parameter-Efficient Sparsity Crafting From Dense to Mixture-of-Experts for Instruction Tuning on General Tasks
Source code of DRAGIN, ACL 2024 main conference Long Paper
Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Retrieval and Retrieval-augmented LLMs
Split text into semantic chunks, up to a desired chunk size. Supports calculating length by characters and tokens, and is callable from Rust and Python.
深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)
A modular graph-based Retrieval-Augmented Generation (RAG) system
Implementation of End-to-End Query Term Weighting (TW-BERT)
LangGPT: Empowering everyone to become a prompt expert!🚀 Structured Prompt,Language of GPT, 结构化提示词,结构化Prompt
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, le…
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Efficient Retrieval Augmentation and Generation Framework
A collection of RAG systems powered by LLM.
整理目前开源的最优表格识别模型,完善前后处理,模型转换为ONNX Organize the currently open-source optimal table recognition models, improve pre-processing and post-processing, and convert the models to ONNX.